Emerging Career Opportunities in Big Data Developer Techie Should know

Unless you have been living under a rock, the term ‘Big Data’ will sound familiar to you. This new buzzword which was coined back in the year 2005 by Oreily Media, is a technology associated with capturing, storing and analysing huge amounts of data sets and thereby extracting information out of same. As easy as that may sound, it requires an immense amount of knowledge and skill to analyze such huge chunks of data. There are big data certification courses which teach you how to effectively extract information from a given data set, utilising special tools and techniques. So if you are thinking of building a career as Big Data Developer, here are the top 7 options for you to consider:

1. Data Scientists

One of the most lucrative career options in the field of big data is becoming a data scientist. A data scientist can be thought of as a ‘king of data science’ who is responsible for mining data from numerous sources and then analysing the same to predict future behaviour. Working along with engineers, statisticians and other IT professionals their job is to identify trends and behaviours which give competitive advantages and hence help businesses flourish. A data scientist can earn anywhere between $89,000 – $100,000 depending upon skills and experience.

Preferred Skillsets – Critical Thinking, Proficient with mathematics, data analysis, risk management and business intuition

2. Data Engineers

One of the other high demand profiles in the big data field is that of a data engineer. A data engineer is responsible for developing and creating architectures which help store and transfer data from one source to other. Generally, a data engineer’s job is to design databases and systems where exabytes of data is stored and collected. They further design algorithms for collecting data as well as conduct quality analysis of the data. It is the system which these engineers build which the data scientists utilise for data analysis and capturing. A data engineer on an average can earn somewhere between $60,000 – $124,000.

Preferred Skillsets – Proficient with MapReduce, Mahout, MATLAB, Java, C++, SQL and other similar tools and languages.

3. Data Visualisation Developer

As can be deciphered from the name itself, a data visualisation developer’s role is to present data in a visual format where it is easy to understand and comprehend. A data visualisation developer often works closely with the data scientists and designs charts, graphs and diagrams using advanced development tools for example D3.js. This, in turn, makes it easy for clients to understand the trends and insights obtained from the analysis and gives them a good understanding of metrics they need to monitor and improve. Though the job sounds easy, it requires extensive technical knowledge and creativity. A data visualisation developer can make around $106,000 – $ 130,000 annually depending on their experience and skill.

Preferred Skillsets – Knowledge of design colour schemes, data-ink ratio, statistics

4. Business Intelligence Engineer

A business intelligence engineer is responsible for managing a data warehouse and at the same time helps turn the analysed data into critical pieces of information which help the businesses make sound decisions. They help create structures and reports of the data which help the decision makers know the key metrics where they need to make improvements and hence come up with strategic plans for business growth. A business intelligence engineer can make anywhere between $95,000 – $137,000 annually depending on skills and knowledge.

Preferred Skillsets – Business acumen, data analysis and modelling, proficiency with BI tools and software like MS Excel, SharePoint etc. Proficiency with relational databases.

5. Business Analytics Specialists

While some people argue that business analytics engineers are pretty much similar to business intelligence engineers, however, there lies a key difference between them. Compared to the business intelligence engineer a business analytics specialist is less involved in deep dive analysis of data and is more focused on the business side. A business analytics specialist utilises tools which interpret the data obtained from intelligence engineers and data scientists and based on these derive insights for business growth. A business analytics specialist can make around $77,000 – $ 130,000 annually and even more depending on the level of growth he can help an organisation achieve.

Preferred Skillsets – Strong interpretation skills, proficient in mathematics, domain expertise, knowledge of languages such as R/ Python etc.

6. Analytics Manager

An analytics manager is responsible for creating strategies and plans based on the reports obtained from business analytics specialists. They operate on relatively low volumes of data and are generally aligned towards the goals and growth of a single organisation. They come up with plans and strategies which helps companies achieve their target within deadlines at minimum cost and with the maximum possibility of profit. Analysing data and delivering results isn’t as easy as it seems and an analytics manager often spends weeks filtering data and coming up with accurate projections. They can make anywhere between $83,00 – $ 134,000 depending upon the country they work in and experience they possess.

Preferred Skillsets – Critical thinking, knowledge of mathematics, report writing and presentation.

7. Machine Learning Engineers

One of the newest career options in the big data field is that of a machine learning engineer. A machine learning engineer tends to possess knowledge of both machine learning as well as big data. They use this skillset of their’s to build solutions and systems which extract information and automatically derive insights from the same with minimum to no human intervention. These systems can thus run 24 hours and 7 days a week and have data being gathered and analysed in real time ensuring authenticity and accuracy at all instants. The solutions they build can be utilised in a single organisation to achieve growth, or they can be embedded a global repository which can be queried by those who need it. Being high in demand this career option pays between $90,000 – $ 140,000 even to freshers who have the required skills.

Preferred Skillsets – Advanced programming, statistics, data modelling, critical thinking.

There are many other similar career options which one can pursue in the big data field with a very fine line of differences between them. Once you complete the big data certification and have the knowledge as well as hands-on experience in mining, extracting and processing data, there is no limitation, and the chances of growth are tremendous.